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Modeling infectious disease dynamics in the complex landscape of global health

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Isaac Newton Institute IDD Collaboration (Including:

Heesterbeek, Hans, Anderson, Roy M., Andreasen, Viggo, Bansal, Shweta, De Angelis, A., Dye, C., Eames, Ken T. D., Edmunds, W. John , Frost, Simon D. W., Funk, S. et al.
). (2015) Modeling infectious disease dynamics in the complex landscape of global health. Science, Volume 347 (Number 6227). doi:10.1126/science.aaa4339

Research output not available from this repository, contact author.
Official URL: http://dx.doi.org/10.1126/science.aaa4339

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Abstract

Despite some notable successes in the control of infectious diseases, transmissibility pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between arthropod vectors, or can survive in environmental reservoirs. Many factors, including behaviour, elevate prevention and control from matters of national policy to international challenge. In the face of this complexity, mathematical models offer valuable tools for synthesizing information to understand epidemiological patterns, and for developing quantitative evidence for decision making in global health.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Divisions: Faculty of Science > Life Sciences (2010- )
Faculty of Science > Mathematics
Journal or Publication Title: Science
Publisher: American Association for the Advancement of Science
ISSN: 0036-8075
Official Date: 13 March 2015
Dates:
DateEvent
13 March 2015Published
Volume: Volume 347
Number: Number 6227
DOI: 10.1126/science.aaa4339
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access

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